With Google Cloud Platform’s autoscaling features and flexible pricing, LogoGrab has ensured that its detection servers can handle peak demands and still keep costs low.

Google Cloud Platform Results

Cut server costs by 45% with flexible pricing

Scaled quickly up and down to meet peak usage with autoscaling

Fine-tuned server performance with flexible resource allocation

By combining an easy-to-use API with powerful image detection technology, LogoGrab generated 1.2 million sales of its brand recognition service within ten months of its commercial launch in 2016. The company’s proprietary technology has several applications from social media brand monitoring to counterfeit detection to retail intelligence, which drew the attention of household names like eBay, Heineken and McDonald’s. As a startup with a growing customer base and a lean, agile mindset, LogoGrab needed an infrastructure that could scale at speed and make every cent count. To do that, it needed Google Cloud Platform (GCP).

Google’s innovative pricing helped LogoGrab cut server costs by 45%.

“When we first looked at Google Cloud Platform, we were very impressed with its flexibility,” says Fintan Halpenny, platform engineer at LogoGrab. “The ability to switch servers on and off with ease, to dynamically allocate resources, to fine tune our system in terms of processors and RAM - that all delivers the scalability that we need. GCP’s flexibility means that we can provide quality to our customers but at the same time stay cost efficient.”

“We have a strong relationship with Google because of the Adopt a Startup programme. The rapport we gained has been invaluable on the tech side and also the marketing side. It makes a lot of sense to continue that relationship. Our future plans are to leverage the advantages that Google has in processing large amounts of data. Google BigQuery is a product we’re looking at right now.”

—Collette Doyle, Marketing Director, LogoGrab

Higher scalability, lower costs

Image recognition is resource intensive. Uploading images, GIFs and videos and running complex algorithms to analyze them requires a great deal of power and storage space. Less than a year after its launch, LogoGrab was analyzing as many as 500 million images a month. The detection servers, the heart of LogoGrab’s service, required more and more investment as the workload grew. Brand detection in social media was proving particularly expensive. Spikes in traffic meant that LogoGgrab would have to pay for extra servers. But prepaid contracts with its existing cloud provider meant that servers stayed on well after they were needed, generating unnecessary costs.

In spring 2017, after participating in Google’s Adopt a Startup programme in Dublin, LogoGrab began to evaluate GCP as an alternative infrastructure for its detection servers. With guidance from Google engineers, LogoGrab was able to map its existing detection stack onto Google Compute Engine instances in under two weeks with zero downtime for its customers. Google Compute Engine’s autoscaling features meant that LogoGrab could quickly ramp up its infrastructure during peak times and then scale back down to normal levels. In those peak times, Google’s flexible pricing plans meant that LogoGrab would only pay for the server time it used. Meanwhile, the parts of the stack that ran constantly generated sustained use discounts, cutting costs even further.

“Autoscaling has become really important for us,” says Fintan. “With social media, for instance, data streamscome in peaks and troughs. And thanks to autoscaling, we adjust our capacity as the peak is happening and then scale back down, allowing us to be cost efficient and not keep servers up too long.”

“When you switch tech, there's always something new to learn but the support from Google's really good. In particular, one of their engineers came to the office, talked us through the challenges we faced and helped us to get a great solution up and running.”

—Fintan Halpenny, Platform Engineer, LogoGrab

Improving the present, planning for the future

Thanks to GCP, LogoGrab was able to cut its infrastructure costs by 45% for its detection servers and continue to provide exemplary service to its customers. With that level of saving, LogoGrab has been able to focus on its business goals instead of managing its infrastructure costs. In addition to growing its customer base, LogoGrab is exploring other Google products like Google BigQuery to provide unique opportunities for data analysis and sharing that information with customers quickly. Google’s range of products will help LogoGrab evolve and improve its service for a long time to come.

“Providing accurate real-time analytics to our customers is a key component of our offering,” says Fintan. “We see Google BigQuery as the most natural tool to aggregate enormous amounts of data without worrying about the underlying architecture. Scalability is what makes Google the best-in-class at any data-driven game.”

About LogoGrab

Founded in 2014, LogoGrab is the world’s leading image recognition technology provider for detecting logos and SKUs in images and video. Its patented Brand Detection API is powered by the proprietary Adaptive Learning Engine, which is benchmarked as having a hit rate, speed, and precision 10X higher than the closest competitor. LogoGrab provides the perfect platform for industries in many verticals, including Social Media Monitoring, Brand Compliance, Counterfeit Detection, Retail Intelligence, Mobile and Brand Engagement, Sponsorship Monitoring, and more. Prestigious clients and partners include: Brandwatch, Earshot, Ebay, DDB Tribal, Geometry Global, MEC, Ogilvy, Nestle, Heineken, Verizon, and McDonald’s.